DocumentCode
2772556
Title
Tracking control of mobile robot using ANFIS
Author
Imen, Masoud ; Mansouri, Mohammad ; Shoorehdeli, Mehdy Aliyari
Author_Institution
Dept. of Mechatron., Eng., Sci. & Res., Branch Islamic Azad Univ., Tehran, Iran
fYear
2011
fDate
7-10 Aug. 2011
Firstpage
422
Lastpage
427
Abstract
This study addresses a nonlinear trajectory tracking control problem for a kinematics Model of nonholonomic mobile robot with considering next 2 time path curvature. The tracking control of mobile robot using two cascade controllers is presented. The first fuzzy controller produces a variable which shows curvature of the path and is considered as one of the inputs of the second fuzzy controller. Adaptive Neuro Fuzzy Inference System (ANFIS) is applied as second stage controller for the solution of the path tracking problem of mobile robots. The inputs value to fuzzy logic layer are VC, C, dR & dθ the robot current linear velocity, trajectory curvature, distance from the robot actual position to the next desired position, and difference between the angles of the dθ and the robot actual heading, respectively. A gradient descent learning algorithm is used to adjust the parameters. That present controller is compared with previous work to confirm its effectiveness.
Keywords
cascade control; control engineering computing; fuzzy control; fuzzy reasoning; gradient methods; learning (artificial intelligence); mobile robots; nonlinear control systems; position control; robot kinematics; adaptive neuro fuzzy inference system; cascade controllers; fuzzy controller; fuzzy logic; gradient descent learning algorithm; kinematics model; nonholonomic mobile robot; nonlinear trajectory tracking control problem; Fuzzy logic; Mathematical model; Mobile robots; Neural networks; Robot kinematics; Trajectory; ANFIS; Cascade Controller; Fuzzy Controller; Look-ahead Curvature; racking Control;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Automation (ICMA), 2011 International Conference on
Conference_Location
Beijing
ISSN
2152-7431
Print_ISBN
978-1-4244-8113-2
Type
conf
DOI
10.1109/ICMA.2011.5985695
Filename
5985695
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